GUEST: Recently I interviewed Clare Gollnick, CTO of Terbium Labs, on the reproducibility crisis in science and its implications for data scientists. The podcast seemed to really resonate with listeners (judging by the number of comments we’ve received via the show notes page and Twitter), for several reasons. To sum up the issue: Many resear…Read More

Google added a feature to its Hire service today designed to help recruiters find past job candidates who weren’t the right people for a previous position but might fit a new gig at a company. When recruiters open a new job, Hire will show them a list of candidates that it thinks are already qualified for the role, based on how their profiles…Read More

VB LIVE: Curating, creating, and delivering fresh content pushes your marketing game to the next level. Your goal: Get the right content to the right people, when and where they want to see it. To learn about how to growthhack content creation, don’t miss this VB Live event. Register here for free. The Associated Press, or AP, is an independent new…Read More

(Reuters) — Twitter said on Wednesday it would no longer allow people to post identical messages from multiple accounts, cracking down on a tactic that Russian agents and others have allegedly used to make tweets or topics go viral.

Artificial intelligence is touted as the future of media buying, allowing for automated analysis of several sources immediately.

“AI capabilities are making ad-spend decisions simpler, more efficient and cost-effective,” said Caroline Klatt, CEO of chatbot technology company Headliner Labs. “It’s a new age, and it will only be a matter of time until digital marketers across the board will be leveraging AI strategically to streamline their workflow.”

But while interest and adoption of AI for media buying is growing, the industry is still grappling with roadblocks. These five charts illustrate the push and pull when it comes to using AI in media buying.

While artificial intelligence applications in business and industry remain limited to narrow machine learning tasks, we are seeing progressive improvements in the convergence of algorithms and hardware that will have significant implications for how well and how quickly we can implement AI. Researchers can now train neural networks within a few hours or days, which opens up an amazing range of possibilities, products, and things to learn — as well as challenges — that we could not have even considered before. Continue reading “7 predictions for the evolution of enterprise AI in 2018”→

In 2017, my team powered chatbots and voice skills for leading brands like Nike, Vice, Jameson, Marriott Rewards, Simon, Gatorade, and more. We witnessed new user behaviors and uncovered an evolved set of best practices to build a chatbot. Here are four actionable learnings from our work that you should consider when launching your own chatbot in 2018.

1. Personalization drives engagement

Bots that are designed to segment and engage customers throughout the entire conversation drive higher metrics than chatbots that do not personalize the conversation. For example, in our testing, personalized results yielded the highest click-through to website, up to 74 percent in some cases.

This year, a leading athletic brand set out to inspire a sneaker style for girls across the globe. The brand launched a customized sneaker builder where the user uploads of a photo of her outfit, and magically, in an instant, the bot pulls up a pair of shoes that matches the uploaded picture. This experience drove a click-through rate 12.5X higher than the global brand average.

Bud Light launched a chatbot with the goal of driving demand and purchase of Bud Light’s team cans on game day throughout the NFL season. A personalized data model and chatbot powered the ordering and delivery of team cans every game day during the NFL season. The Bud Light chatbot acted as a utility to remind fans that it was game time, and to order Bud Light before the game. Bud Light saw an 83 percent engagement rate with personalization.

2. Get to the point quickly

Across multiple chatbots, about half of the first actions that users take is free text entry. Updating the onboarding copy to manage expectations — “this is a bot that can do X and Y,” for example — lowers that initial friction. If the first intent is help-related or a long-form text entry, you can provide a customer service number, FAQs, or an option to “talk to a human” from the very beginning.

When users get into the designed experience, point of sale should be within five clicks. For example, after A/B testing a chatbot across 250,000 users, we noticed a significant drop-off occured when the core focus (click to purchase, etc.) was beyond five clicks.

3. Chatbots go beyond mobile devices

Bots are an effective tool to drive real-world activities or offline conversions, with coupon redemption rates as high as 30 percent.

A leading quick-service restaurant brand launched a new bot that drove users through an immersive content experience with videos, quizzes, recipes, and coupons. This high engagement led to over 71,000 coupons redeemed from the chatbot.

The Jordan Brand aimed to reach elite high school football, basketball, and baseball athletes with an ongoing training chatbot experience for pre-season training. Jordan delivered nightly prep videos and daily workout series to a targeted group of high school athletes in advance of basketball season on Facebook Messenger. Athletes loved receiving push notifications reminding them to work out. Jordan saw an extremely high completion rate as well as a high re-engagement rate compared to regular customer relationship management programs: Over 70 percent of users surveyed enjoyed the experience.

4. Truly understand your users

Understanding why people did or did not enjoy the experience is key. One way to do this is using free text analysis to understand sentiment and drop-off. For example, we launched a new bot with a leading shoe retailer. Most people came to the bot knowing what specific shoe they wanted to buy or with a question about the shoe they already bought. Cater to the specific pain points and make sure your bot handles customer intent at every stage.

Finally, make sure to survey users and learn from both your best purchasers as well as your qualified no’s. One way to do this by asking your users directly. You can use a chatbot for net promoter score surveying.

Jonathan Shriftman is the director of business development at Snaps, a mobile messaging service.

The year 2020 is just three years away, and technologies are aligning for a perfect storm that could either make or break established media houses. Live video, Virtual Reality, Artificial Intelligence, and Augmented Reality have all been buzzwords of the “next big thing.” As standalone products, none of these have been the silver bullet. But at the intersection of all these technologies, new storytelling formats and platforms are emerging that will fundamentally shift the way we publish.

In my final blog post of the year, I’m going to talk about some of the developments in librarianship and the related domains that caught my eye. Of course, this is by necessity going to be personal and idiosyncratic from my point of view“Obi-Wan: Anakin, Chancellor Palpatine is evil!Anakin Skywalker: From my point of view, the Jedi are evil!” – Revenge of the Sith (2005)Continue reading “My roundup of developments in 2017 that caught my eye.”→